Several problem areas need to be addressed when making color negative paper prints from color negative film images. The object of the process is to make a pleasing print from the film image. The first problem is to find the level of exposure necessary in a projection printer system to produce that pleasing print. In the simplest implementation of a process, one projects the color negative film image onto a photosensitive paper image receiver, processes the paper, and then repeats the process until a pleasing print has been obtained. In automated photo-finishing operations, a film scanner reads densities from the negative and passes the information to a computer algorithm that computes the appropriate exposure values so that a pleasing print can be obtained. At this point, the conventional photographic printing process ends. That is, if there are any remaining problems in a photographic image, no other simple processes are available to reduce the severity of the problem. Problems such as inappropriate gamma for a particular scene, poor quality camera or printer lenses, low or high activity of film or paper processes, poor scene balance, and poor sharpness in the final image remain that we would like to correct or modify.
Methods and systems have been described for more than 10 years that are devoted to producing pictorial images on various media and devices from scenes captured on photographic film, via scanning to produce a digital image, image processing, and output rendering. Examples include the following.
Journal of Imaging Technology, Vol. 14, Number 3, June 1988, Firth et. al. describe systems that capture scenes on film, scan film to produce a digital image, digitally process the image, and output via a laser AgX printer.
U.S. Pat. No. 4,500,919, Schreiber discloses an image reproduction system that scans an image captured on film, displays the image on a video monitor, enables image processing, and finally output to an inked hardcopy.
U.S. Pat. No. 4,979,032 (Dec. 18, 1990, filing date: Dec. 27, 1988), Alessi et al. describe an apparatus, including a film scanner, an video monitor, image processing, and output, to produce various output visually matched to the image displayed on the monitor.
U.S. Pat. No. 5,267,030, issued Nov. 30, 1993, inventors Giorgianni et. al. describe method and means to transform images captured on film, via digitization on a film scanner, to a color metric or other space, with output onto a variety of media and devices. This document describes the improvements offered by digital image processing, including aesthetically pleasing modifications to the tone and color reproduction as well as sharpening.
U.S. Pat. No. 5,300,381, issued Apr. 5, 1994, inventors Buhr et. al. describe a pictorial imaging system that consists of capture on photographic film, film scanning to produce a digital image, image processing, and digital output.
U.S. Pat. No. 5,579,132, issued Nov. 26, 1996, inventor Takahashi describes an image processing system devoted to storing or producing images that have "substantially the same color" or additional "aesthetic color correction" versus the original scene, based on a variety of image processing transformations of the digitized image.
U.S. Pat. No. 5,608,542, issued Mar. 4, 1997, inventors Krahe et. al. describe a system that produces index prints based on scanning a film frame, image processing, and rendering.
U.S. Pat. No. 4,945,406, issued Jul. 31, 1990, inventor Cok, describes a system for achieving automatic color balancing of color images by transferring color pixel values from log exposure RGB color values into printing density values and generating color correction offset values utilizing a printing density based color correction method.
The KODAK 35 mm/24 mm color negative film format Index Printer, sold by Kodak, produces an index print (a matrix of small imagettes) reproduced from individual film image frames. The index print is produced by the photofinisher when the original print order is processed and is supplied to the customer as a convenient means of identifying image frames on the film (see: U.S. Pat. No. 5,608,542, above). The Kodak Index Printer uses image processing on the miniature images including:
digital image in film RGB printing density PA1 applying a scene balance algorithm to balance the digital film printing density image PA1 mapping the color negative digital image onto a color paper (EDGE-type) characteristic curve PA1 digital sharpening PA1 rendering using a CRT printer onto photographic paper
In the Index Printer, the above image processing: (1) is not applied to full frame images in a digital color printer; and (2) is not applied to high resolution images in a digital color printer, only low resolution images.
U.S. Pat. No. 5,012,333, issued Apr. 30, 1991, inventors Lee et al., discloses a dynamic range adjustment system for printing digital images based on visual photoreceptor adaption and human visual contrast sensitivity. The system adjusts the contrast of the low frequency component only of the image, preserving the high frequency component in its contrast.
It is also possible to improve the tone reproduction of a captured scene using another approach. The captured image contrast is first estimated by (1) forming a Laplacian histogram, (2) determining, from the Laplacian histogram, the first and second thresholds which eliminate substantially uniform areas or a substantially textured portion of the digital image, (3) selecting pixels which are based on the first and second thresholds from the digital image, (4) forming a histogram from the sampled pixels, (5) computing a standard deviation of the sampled histogram, and (6) estimating the contrast of the digital image by comparing the computed standard deviation with a predetermined contrast for determining contrast of the input image in relationship with the predetermined contrast. The captured scene contrast estimate can be adjusted to be that of an aim scene contrast, forming a correction function, and the tone scale of the captured scene can be remapped using this correction function.
U.S. Pat. No. 4,731,671 teaches a method for contrast adjustment in digital image processing. This method creates a plurality of predetermined Laplacian response intervals and then computes the Laplacian for each pixel in an input image. The code value for each pixel in the image is then placed in its corresponding Laplacian response interval for accumulating several code value histograms, one for each Laplacian response interval. It then selects the histogram whose shape is closest to a normal distinct standard deviation of the selected histogram is taken as an estimate of the scene contrast. The standard deviation is used as an estimate of the scene contrast because of the correlation between the standard deviation and the scene contrast. That is, a high standard deviation corresponds to a high scene contrast and a low standard deviation corresponds to a low scene contrast.
The estimated contrast is then compared with a distribution of scene contrasts (e.g., standard deviations from a plurality of scenes) pre-computed from a plurality of random sample of images. If the estimated contrast is higher than the population average, then the image is considered to have a higher than normal contrast and the system reproduction contrast is then adjusted lower so that the printed image will have an image contrast that is closer to the average contrast. If the estimated image contrast is lower than the average, then the system reproduction contrast is raised accordingly.
The method of U.S. Pat. No. 4,654,722 seems to perform rather well for most images; however, there are a few situations when there are shortcomings. First, there are two parameters that have to be predetermined: the lower threshold and the width of the Laplacian interval. The patent does not provide an automatic method for setting these two parameters. As a consequence, for some images, the lower threshold is not high enough to exclude noise and textures, therefore, causing the standard deviation of the selected histogram to be unduly biased by large uniform areas (when the noise is higher than the lower threshold) or by busy texture areas (such as grass or trees). Secondly, the selected histogram often exhibits bimodality for overcast scenes with sky in them. Although the scene contrast is low, the standard deviation of the selected histogram is large because of the bimodality caused by the dark grass pixels and the bright sky pixels.
A theoretical construct is described by W. A. Richards, "Lightness Scale from Image Intensity Distribution," Applied Optics, 21, 14, pp. 2569-2582, 1982. The idea is that a "randomly" sampled log-exposure histogram of an image should have a shape similar to a normal distribution.
In addition, the above-described histogram transformation method does not have a sound theoretical foundation, and frequently, it produces unacceptable tone reproduction for consumer images. Still further, in the method of W. A. Richards, a drawback arises in defining what constitutes a truly random sampling. Furthermore, another drawback of the histogram modification approach in the prior art is that the resulting tone transformation curve often has too high or too low local contrast in some portions of the curve. Therefore, the processed image does not look pleasing.
All of these articles or patents describe, in one form or another, processes for obtaining more pleasing prints from a film image capture than the conventional optical process. There is thus a need for a solution to these problems, which can be incorporated into a digital photofinishing system.